Recent severe earthquakes, such as the 2010-2011 Christchurch earthquake series, have put emphasis on building resilience all over the world. To achieve such resilience, procedures for low damage seismic design have been developed to satisfy both life safety requirements and the need to minimize undesirable economic effects of required building repair or structural member replacement following a major earthquake. Seismic resisting systems following this concept are expected to withstand severe earthquakes without requiring major post-earthquake repairs, using isolating mechanisms or sacrificial systems that either do not need repair or are readily repairable or replaceable. These include the sliding hinge joint with asymmetric friction connections (SHJAFCs) in beam-to-column connections of the moment resisting steel frames (MRSFs) and symmetric friction connections (SFCs) in braces of the braced frames. A 9 m tall, configurable three-storey steel framed composite floor building incorporating frictionbased connections is to be tested using two linked bi-directional shake tables at the International joint research Laboratory of Earthquake Engineering (ILEE) facilities, Shanghai, China. The structural systems are configurable, allowing different moment and braced frame structural systems tested in two horizontal directions. The structure is designed and detailed to undergo, at worst, minor damage under a planned series of severe earthquakes.
Shaking table testing of a full-scale three storey resilient and reparable complete composite steel framed building system is being conducted. The building incorporates a number of interchangeable seismic resisting systems of New Zealand and Chinese origin. The building has a steel frame and cold formed steel-concrete composite deck. Energy is dissipated by means of friction connections. These connections are arranged in a number of structural configurations. Typical building nonskeletal elements (NSEs) are also included. Testing is performed on the Jiading Campus shaking table at Tongji University, Shanghai, China. This RObust BUilding SysTem (ROBUST) project is a collaborative China-New Zealand project sponsored by the International Joint Research Laboratory of Earthquake Engineering (ILEE), Tongji University, and a number of agencies and universities within New Zealand including BRANZ, Comflor, Earthquake Commission, HERA, QuakeCoRE, QuakeCentre, University of Auckland, and the University of Canterbury. This paper provides a general overview of the project describing a number of issues encountered in the planning of this programme including issues related to international collaboration, the test plan, and technical issues.
Rapid, accurate structural health monitoring (SHM) assesses damage to optimise decision-making. Many SHM methods are designed to track nonlinear stiffness changes as damage. However, highly nonlinear pinched hysteretic systems are problematic in SHM. Model-based SHM often fails as any mismatch between model and measured response dynamics leads to significant error. Thus, modelfree methods of hysteresis loop tracking methods have emerged. This study compares the robustness and accuracy in the presence of significant measurement noise of the proven hysteresis loop analysis (HLA) SHM method with 3 emerging model-free methods and 2 further novel adaptations of these methods using a highly nonlinear, 6-story numerical structure to provide a known ground-truth. Mean absolute errors in identifying a known nonlinear stiffness trajectory assessed at four points over two successive ground motion inputs from September 2010 and February 2011 in Christchurch range from 1.71-10.52%. However, the variability is far wider with maximum errors ranging from 3.90-49.72%, where the second largest maximum absolute error was still 19.74%. The lowest mean and maximum absolute errors were for the HLA method. The next best method had mean absolute error of 2.92% and a maximum of 10.51%. These results show the clear superiority of the HLA method over all current emerging model-free methods designed to manage the highly nonlinear pinching responses common in reinforced concrete structures. These results, combined with high robustness and accuracy in scaled and fullscale experimental studies, provide further validation for using HLA for practical implementation.
Recent tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural mitigation, warning systems, education and evacuation planning). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and evacuation behaviour is rare when compared to findings for evacuations from other hazards. More knowledge is required to document the full evacuation process, including responses to warnings, pre-evacuation actions, evacuation dynamics, and the return home. Tsunami evacuation modelling has the potential to inform evidence-based tsunami risk planning and response. However, to date, tsunami evacuation models have largely focused on the timings of evacuations, rather than behaviours of those evacuating. In this research, survey data was gathered from coastal communities in Banks Peninsula and Christchurch, New Zealand, relating to behaviours and actions during the November 14th 2016 Kaikōura earthquake tsunami. Survey questions asked about immediate actions following the earthquake shaking, reactions to tsunami warnings, pre-evacuation actions, evacuation dynamics and details on congestion. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour, and was further used to develop a realistic evacuation model prototype to evaluate the capacity of the roading network in Banks Peninsula during a tsunami evacuation. The evacuation model incorporated tsunami risk management strategies that have been implemented by local authorities, and exposure and vulnerability data, alongside the empirical data collected from the survey. This research enhances knowledge of tsunami evacuation behaviour and reactions to tsunami warnings, and can be used to refine evacuation planning to ensure that people can evacuate efficiently, thereby reducing their tsunami exposure and personal risk.
Recent global tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural defences, warning systems, education and evacuation measures). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and tsunami evacuation behaviour is rare when compared to findings about evacuations to avoid other sources of hazard. To date empirical research into tsunami evacuations has focused on evacuation rates, rather than other aspects of the evacuation process. More knowledge is required about responses to warnings, pre-evacuation actions, evacuation dynamics and the return home after evacuations. Tsunami evacuation modelling has the potential to inform evidence-based tsunami risk planning and response. However to date tsunami evacuation models have largely focused on timings of evacuations, rather than evacuation behaviours. This Masters research uses a New Zealand case study to reduce both of these knowledge gaps. Qualitative survey data was gathered from populations across coastal communities in Banks Peninsula and Christchurch, New Zealand, required to evacuate due to the tsunami generated by the November 14th 2016 Kaikōura Earthquake. Survey questions asked about reactions to tsunami warnings, actions taken prior to evacuating and movements during the 2016 tsunami evacuation. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour. Finally, it was used to develop an evacuation model for Banks Peninsula. Where appropriate, the modelling inputs were informed by the survey data. Three key findings were identified from the results of the evacuation behaviour survey. Although 38% of the total survey respondents identified the earthquake shaking as a natural cue for the tsunami, most relied on receiving official warnings, including sirens, to prompt evacuations. Respondents sought further official information to inform their evacuation decisions, with 39% of respondents delaying their evacuation in order to do so. Finally, 96% of total respondents evacuated by car. This led to congestion, particularly in more densely populated Christchurch city suburbs. Prior to this research, evacuation modelling had not been completed for Banks Peninsula. The results of the modelling showed that if evacuees know how to respond to tsunami warnings and where and how to evacuate, there are no issues. However, if there are poor conditions, including if people do not evacuate immediately, if there are issues with the roading network, or if people do not know where or how to evacuate, evacuation times increase with there being more bottlenecks leading out of the evacuation zones. The results of this thesis highlight the importance of effective tsunami education and evacuation planning. Reducing exposure to tsunami risk through prompt evacuation relies on knowledge of how to interpret tsunami warnings, and when, where and how to evacuate. Recommendations from this research outline the need for public education and engagement, and the incorporation of evacuation signage, information boards and evacuation drills. Overall these findings provide more comprehensive picture of tsunami evacuation behaviour and decision making based on empirical data from a recent evacuation, which can be used to improve tsunami risk management strategies. This empirical data can also be used to inform evacuation modelling to improve the accuracy and realism of the evacuation models.
